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2016 | OriginalPaper | Buchkapitel

Applying Social Network Analysis and Centrality Measures to Improve Information Flow Analysis

verfasst von : Stephan Kiesling, Jil Klünder, Diana Fischer, Kurt Schneider, Kai Fischbach

Erschienen in: Product-Focused Software Process Improvement

Verlag: Springer International Publishing

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Abstract

In software development projects, documents are very important for sharing requirements and other information among employees. However, information can be transported in different ways. Conversations, meetings, workshops and emails convey and impart information as well. Especially large companies struggle in dealing with unclear and incorrect information flows. These information flows can be improved by means of information flow analysis and flow patterns. One technique to analyze information flows is the FLOW method. It supports visualization and analysis of information flows to detect lacks and anomalies and thereby improves information flows. An analyst gathers information transported in the company. Afterwards, information flows are visualized and analyzed based on patterns and personal experience. Nevertheless, analysis based on individual knowledge is error-prone. Hence, we improve the FLOW method with the help of social network analysis applying centrality measures to the FLOW method and to support the FLOW analyst.

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Fußnoten
1
Refer to [16] for a detailed description of the FLOW syntax.
 
2
UCINET is a common used tool for social network analysis.
 
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Metadaten
Titel
Applying Social Network Analysis and Centrality Measures to Improve Information Flow Analysis
verfasst von
Stephan Kiesling
Jil Klünder
Diana Fischer
Kurt Schneider
Kai Fischbach
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-49094-6_25